Co-occurring keywords · papers mentioning both
Papers
Reinforcement Learning based Disease Progression Model for Alzheimer’s Disease
NeurIPS 2021
A General System of Differential Equations to Model First-Order Adaptive Algorithms
JMLR 2020
Analog Accelerator for Simulation and Diagnostics
AAAI 2020
Deep Energy-based Modeling of Discrete-Time Physics
NeurIPS 2020
Deep Learning For Symbolic Mathematics
ICLR 2020
Differential Equation Units: Learning Functional Forms of Activation Functions from Data
AAAI 2020
Acceleration via Symplectic Discretization of High-Resolution Differential Equations
NeurIPS 2019
A Dynamical Systems Perspective on Nesterov Acceleration
ICML 2019
Beyond Structural Causal Models: Causal Constraints Models
UAI 2019
Convergence-Rate-Matching Discretization of Accelerated Optimization Flows Through Opportunistic State-Triggered Control
NeurIPS 2019
Algorithmic Linearly Constrained Gaussian Processes
NeurIPS 2018
Beyond Finite Layer Neural Networks: Bridging Deep Architectures and Numerical Differential Equations
ICML 2018
Constrained Cross-Entropy Method for Safe Reinforcement Learning
NeurIPS 2018
Deep Learning for Physical Processes: Incorporating Prior Scientific Knowledge
ICLR 2018
Neural Networks Trained to Solve Differential Equations Learn General Representations
NeurIPS 2018
The Physical Systems Behind Optimization Algorithms
NeurIPS 2018
Predicting User Activity Level In Point Processes With Mass Transport Equation
NeurIPS 2017
Principles of Riemannian Geometry in Neural Networks
NeurIPS 2017
A Differential Equation for Modeling Nesterov's Accelerated Gradient Method: Theory and Insights
JMLR 2016
Fast Parameter Inference in Nonlinear Dynamical Systems using Iterative Gradient Matching
ICML 2016
A Differential Equation for Modeling Nesterov’s Accelerated Gradient Method: Theory and Insights
NeurIPS 2014
Probabilistic Solutions to Differential Equations and their Application to Riemannian Statistics
AISTATS 2014
Spike timing-dependent plasticity as dynamic filter
NeurIPS 2010
Accelerating Bayesian Inference over Nonlinear Differential Equations with Gaussian Processes
NeurIPS 2008